Design and Development of Model Predictive Primary Control of Micro Grids. Simulation Examples in MATLAB

170 Pages·2023·5.142 MB·English

by  Puvvula Vidyasagar, K. Shanti Swarup

Springer Tracts in Electrical and Electronics Engineering
Puvvula Vidyasagar 
K. Shanti Swarup
Design and Development
of Model Predictive
Primary Control of
Micro Grids
Simulation Examples in MATLAB
Springer Tracts in Electrical and Electronics
Engineering
Series Editors
Brajesh Kumar Kaushik, Department of Electronics and Communication
Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India
Mohan Lal Kolhe, Department of Engineering & Science, University of Agder,
Kristiansand, Norway
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·
Puvvula Vidyasagar K. Shanti Swarup
Design and Development
of Model Predictive Primary
Control of Micro Grids
Simulation Examples in MATLAB
Puvvula Vidyasagar K. Shanti Swarup
Department of Electrical Engineering Department of Electrical Engineering
Indian Institute of Technology Madras Indian Institute of Technology Madras
Chennai, Tamil Nadu, India Chennai, Tamil Nadu, India
ISSN 2731-4200 ISSN 2731-4219 (electronic)
Springer Tracts in Electrical and Electronics Engineering
ISBN 978-981-19-5851-9 ISBN 978-981-19-5852-6 (eBook)
https://doi.org/10.1007/978-981-19-5852-6
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature
Singapore Pte Ltd. 2023
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Contents
1 Micro-grid Introduction and Overview ........................... 1
1.1 Conventional Power Systems Review ......................... 1
1.2 Concept of Distributed Generation ........................... 4
1.3 Necessity of Distributed Generation .......................... 5
1.4 Single DG Challenges ...................................... 7
1.5 Concept of Micro-grid and Definitions ....................... 8
1.6 General Constituents of a Micro-grid ......................... 11
1.7 Advantages of a Micro-grid ................................. 16
1.8 Micro-grid Challenges ..................................... 16
1.9 Micro-grid Operational Modes .............................. 17
1.10 Key Takeaways ........................................... 18
References ..................................................... 18
2 An Overview of Micro-grid Control .............................. 21
2.1 Control Objectives in a Micro-grid ........................... 21
2.2 Control Architectures in a Micro-grid ........................ 23
2.3 Hierarchical Control of a Standalone Micro-grid ............... 25
2.3.1 Primary Control .................................... 26
2.3.2 Secondary Control .................................. 30
2.3.3 Tertiary Control .................................... 33
2.4 Key Takeaways ........................................... 33
References ..................................................... 34
3 Mathematical Modelling of a Micro-grid ......................... 37
3.1 Micro-grid Description and Reference Frames ................. 37
3.2 Synchronous-DG Model .................................... 40
3.3 EI-DG Model ............................................. 43
3.3.1 AC Side Dynamics of the EI-DG in abc Frame .......... 43
3.3.2 AC Side Dynamics of the EI-DG in Its Local d3-q3
Frame ............................................. 45
3.3.3 Phase-Locked Loop Dynamics ........................ 45
3.3.4 DC Side Dynamics of the EI-DG ...................... 46
v
vi Contents
3.4 Load Modelling in the Micro-grid ........................... 48
3.5 Network Modelling in the Micro-grid ........................ 49
3.6 Complete Model of the Grid-Connected Micro-grid ............ 50
3.7 Complete Model of the Standalone Micro-grid ................. 51
3.8 Key Takeaways ........................................... 52
References ..................................................... 52
4 Introduction to Model Predictive Control ......................... 53
4.1 MPC Description .......................................... 53
4.2 Advantages of MPC ....................................... 54
4.3 MPC Types ............................................... 54
4.4 Linear Model-Based MPC/Linear-MPC/L-MPC ............... 56
4.4.1 Augmented Model .................................. 57
4.4.2 Prediction Vector Within the Prediction Horizon ......... 58
4.4.3 Optimal Control Problem Formulation ................. 59
4.5 Nonlinear Model-Based MPC/Nonlinear-MPC/N-MPC ......... 60
4.6 Brief Review of MPC in Power Engineering ................... 61
4.7 Micro-grid MPC Methodologies Discussed in the Book ......... 63
4.8 Key Takeaways ........................................... 65
References ..................................................... 66
5 LTI-MPC for the Micro-grid Control ............................ 69
5.1 Mathematical Formulation of the LTI-MPC ................... 69
5.1.1 Augmented Model .................................. 70
5.1.2 Prediction Vector Within the Prediction Horizon ......... 71
5.1.3 Optimal Control Problem Formulation ................. 72
5.2 LTI-MPC for the Micro-grid Control ......................... 74
5.2.1 Role of Each DG Unit in the Micro-grid Control ........ 74
5.2.2 Operational Constraints .............................. 75
5.2.3 Choice of the Controller Parameters ................... 75
5.3 Performance Analysis ...................................... 78
5.4 Key Takeaways ........................................... 89
References ..................................................... 89
6 LTV-MPC with Extended “TAIL” ............................... 91
6.1 Mathematical Formulation of the LTV-MPC ................... 91
6.1.1 Prediction of the Forced Response ..................... 92
6.1.2 Prediction of the Natural Response .................... 94
6.1.3 Optimal Control Problem Formulation ................. 95
6.1.4 Choice of the Input Reference Trajectories V (t) ....... 96
ref
6.2 Performance Analysis ...................................... 97
6.3 Key Takeaways ........................................... 104
References ..................................................... 107
Contents vii
7 Special Functions in the MPC Formulation ....................... 109
7.1 Role of Orthonormal Special Functions in the MPC ............ 109
7.2 Approximation of the Original Control Trajectories ............ 110
7.2.1 Laguerre Functions .................................. 110
7.2.2 Kautz Functions .................................... 111
7.3 Mathematical Formulation of the LTI-MPC Using Special
Functions ................................................ 114
7.3.1 Augmented Model .................................. 114
7.3.2 LTI-MPC Using Special Functions .................... 115
7.4 Mathematical Formulation of the LTV-MPC Using Special
Functions ................................................ 117
7.4.1 Augmented Model .................................. 117
7.4.2 Prediction of the Natural Response .................... 120
7.4.3 LTV-MPC Using Special Functions .................... 120
7.4.4 Choice of the Input Reference Trajectories V (t) ....... 122
ref
7.5 Performance Analysis ...................................... 123
7.5.1 Choice of the Laguerre and Kautz Network
Parameters ......................................... 123
7.6 Key Takeaways ........................................... 124
References ..................................................... 131
8 Auxiliary Requirements for Real-Time Implementation ............ 133
8.1 Scalability ................................................ 133
8.2 Harmonics ............................................... 134
8.3 State Estimation ........................................... 135
8.4 Choice of a Particular MPC Formulation ...................... 135
8.4.1 Computational Complexity ........................... 135
8.4.2 Performance Point of View ........................... 136
8.5 Robustness ............................................... 136
8.5.1 Disturbance Compensator ............................ 136
8.5.2 Mathematical Formulation of the Robust LTI-MPC ...... 138
8.5.3 Mathematical Formulation of the Robust LTI-MPC
with Special Functions ............................... 141
8.6 Performance Analysis of the Robust LTI-MPC ................. 143
8.7 Key Takeaways ........................................... 146
References ..................................................... 148
9 Conclusion and Future Scope .................................... 149
9.1 Summary of the Book ...................................... 149
9.2 Novel Concepts in the Book ................................ 151
9.3 Limitations ............................................... 152
9.4 Future Scope ............................................. 153
Appendix 1 ..................................................... 153
Appendix 2 ..................................................... 155
About the Authors
Puvvula Vidyasagar completed his Ph.D. from Indian Institute of Technology (IIT)
Madras. He completed his M.Tech. from National Institute of Technology (NIT)
Calicut and B.Tech. degree from RVR&JC Engineering College, India. His research
interests are power systems analysis and control, smart grids, renewable energy
technologies, micro grids, and power systems modelling. He has several research
papers in journals and conferences published to his credit.
K. Shanti Swarup is a faculty with the Department of Electrical Engineering, Indian
Institute of Technology (IIT) Madras, India. Before joining the department as a
visiting faculty member, he held positions at the Mitsubishi Electric Corporation,
Osaka, Japan, and Kitami Institute of Technology, Hokkaido, Japan, serving as a
visiting research scientist and visiting professor, respectively, from 1992 to 1999.
Since 2000, he has been a professor at IIT Madras. His research areas include
power systems, smart grids, artificial intelligence, knowledge-based systems, compu-
tational intelligence, soft computing, Energy Management Systems (EMS), Supervi-
sory Control and Data Acquisition (SCADA), power system automation, and network
protection. He has done research projects with various industries like BHEL, Hitachi,
Easun-MR, etc.
ix
Abbreviations
AC Alternating Current
DC Direct Current
DER Distributed Energy Resource
DG Distributed generator
DMC Dynamic Matrix Control
FIR Finite Impulse Response
GPC Generalized Predictive Control
IM Induction Motor
kV Base kV
b
L-MPC Linear model-based MPC
LQR Linear Quadratic Regulator
LTI Linear Time-Invariant
LTI-MPC Linear Time-Invariant Model Predictive Controller
LTV Linear Time-Variant
LTV-MPC Linear Time-Variant Model Predictive Controller
MPC Model Predictive Controller
MPPT Maximum Power Point Tracking
MVA Base MVA
b
N-MPC Nonlinear model-based MPC
OAT One At a Time
PCC Point of Common Coupling
P-f Active power versus Frequency
PI Proportional Integral
PID Proportional Integral Derivative
PLL Phase Locked Loop
PR Proportional Resonant
PV Photovoltaic
PV-DG Photovoltaic Distributed Generator
PWM Pulse Width Modulator
Q-V Reactive power versus Voltage
R-L Impedance load
xi